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  2. Tree diagram (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Tree_diagram_(probability...

    In probability theory, a tree diagram may be used to represent a probability space. A tree diagram may represent a series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck, without replacing the cards). [1] Each node on the diagram represents an event and is associated with the ...

  3. Urn problem - Wikipedia

    en.wikipedia.org/wiki/Urn_problem

    binomial distribution: the distribution of the number of successful draws (trials), i.e. extraction of white balls, given n draws with replacement in an urn with black and white balls. [3] Hoppe urn: a Pólya urn with an additional ball called the mutator. When the mutator is drawn it is replaced along with an additional ball of an entirely new ...

  4. Tree diagram - Wikipedia

    en.wikipedia.org/wiki/Tree_diagram

    Tree diagram (probability theory), a diagram to represent a probability space in probability theory; Decision tree, a decision support tool that uses a tree-like graph or model of decisions and their possible consequences; Event tree, inductive analytical diagram in which an event is analyzed using Boolean logic; Game tree, a tree diagram used ...

  5. File:Probability tree diagram.svg - Wikipedia

    en.wikipedia.org/wiki/File:Probability_tree...

    You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. ... Conditional probability; Tree diagram ...

  6. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    Probability is the branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1] [1] [2] A simple example is the tossing of a fair (unbiased) coin. Since the ...

  7. Probability axioms - Wikipedia

    en.wikipedia.org/wiki/Probability_axioms

    The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. [1] These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases. [2] There are several other (equivalent) approaches to formalising ...

  8. Mutual exclusivity - Wikipedia

    en.wikipedia.org/wiki/Mutual_exclusivity

    The probability of drawing a red and a club in two drawings without replacement is then 26/52 × 13/51 × 2 = 676/2652, or 13/51. With replacement, the probability would be 26/52 × 13/52 × 2 = 676/2704, or 13/52. In probability theory, the word or allows for the possibility of both events happening

  9. Bernoulli trial - Wikipedia

    en.wikipedia.org/wiki/Bernoulli_trial

    Graphs of probability P of not observing independent events each of probability p after n Bernoulli trials vs np for various p.Three examples are shown: Blue curve: Throwing a 6-sided die 6 times gives a 33.5% chance that 6 (or any other given number) never turns up; it can be observed that as n increases, the probability of a 1/n-chance event never appearing after n tries rapidly converges to 0.